README.md 16.2 KB
Newer Older
limm's avatar
limm committed
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
<div align="center">
  <img src="https://raw.githubusercontent.com/open-mmlab/mmcv/master/docs/en/mmcv-logo.png" width="300"/>
  <div>&nbsp;</div>
  <div align="center">
    <b><font size="5">OpenMMLab website</font></b>
    <sup>
      <a href="https://openmmlab.com">
        <i><font size="4">HOT</font></i>
      </a>
    </sup>
    &nbsp;&nbsp;&nbsp;&nbsp;
    <b><font size="5">OpenMMLab platform</font></b>
    <sup>
      <a href="https://platform.openmmlab.com">
        <i><font size="4">TRY IT OUT</font></i>
      </a>
    </sup>
  </div>
  <div>&nbsp;</div>
</div>
xiabo's avatar
xiabo committed
21

limm's avatar
limm committed
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
[![docs](https://img.shields.io/badge/docs-latest-blue)](https://mmcv.readthedocs.io/en/latest/)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/mmcv)](https://pypi.org/project/mmcv/)
[![PyPI](https://img.shields.io/pypi/v/mmcv)](https://pypi.org/project/mmcv)
[![badge](https://github.com/open-mmlab/mmcv/workflows/build/badge.svg)](https://github.com/open-mmlab/mmcv/actions)
[![codecov](https://codecov.io/gh/open-mmlab/mmcv/branch/master/graph/badge.svg)](https://codecov.io/gh/open-mmlab/mmcv)
[![license](https://img.shields.io/github/license/open-mmlab/mmcv.svg)](https://github.com/open-mmlab/mmcv/blob/master/LICENSE)

English | [简体中文](README_zh-CN.md)

## Introduction

MMCV is a foundational library for computer vision research and supports many
research projects as below:

- [MIM](https://github.com/open-mmlab/mim): MIM installs OpenMMLab packages.
- [MMClassification](https://github.com/open-mmlab/mmclassification): OpenMMLab image classification toolbox and benchmark.
- [MMDetection](https://github.com/open-mmlab/mmdetection): OpenMMLab detection toolbox and benchmark.
- [MMDetection3D](https://github.com/open-mmlab/mmdetection3d): OpenMMLab's next-generation platform for general 3D object detection.
- [MMRotate](https://github.com/open-mmlab/mmrotate): OpenMMLab rotated object detection toolbox and benchmark.
- [MMSegmentation](https://github.com/open-mmlab/mmsegmentation): OpenMMLab semantic segmentation toolbox and benchmark.
- [MMOCR](https://github.com/open-mmlab/mmocr): OpenMMLab text detection, recognition, and understanding toolbox.
- [MMPose](https://github.com/open-mmlab/mmpose): OpenMMLab pose estimation toolbox and benchmark.
- [MMHuman3D](https://github.com/open-mmlab/mmhuman3d): OpenMMLab 3D human parametric model toolbox and benchmark.
- [MMSelfSup](https://github.com/open-mmlab/mmselfsup): OpenMMLab self-supervised learning toolbox and benchmark.
- [MMRazor](https://github.com/open-mmlab/mmrazor): OpenMMLab model compression toolbox and benchmark.
- [MMFewShot](https://github.com/open-mmlab/mmfewshot): OpenMMLab fewshot learning toolbox and benchmark.
- [MMAction2](https://github.com/open-mmlab/mmaction2): OpenMMLab's next-generation action understanding toolbox and benchmark.
- [MMTracking](https://github.com/open-mmlab/mmtracking): OpenMMLab video perception toolbox and benchmark.
- [MMFlow](https://github.com/open-mmlab/mmflow): OpenMMLab optical flow toolbox and benchmark.
- [MMEditing](https://github.com/open-mmlab/mmediting): OpenMMLab image and video editing toolbox.
- [MMGeneration](https://github.com/open-mmlab/mmgeneration): OpenMMLab image and video generative models toolbox.
- [MMDeploy](https://github.com/open-mmlab/mmdeploy): OpenMMLab model deployment framework.

It provides the following functionalities.

- Universal IO APIs
- Image/Video processing
- Image and annotation visualization
- Useful utilities (progress bar, timer, ...)
- PyTorch runner with hooking mechanism
- Various CNN architectures
- High-quality implementation of common CUDA ops

It supports the following systems.

- Linux
- Windows
- macOS

See the [documentation](http://mmcv.readthedocs.io/en/latest) for more features and usage.

Note: MMCV requires Python 3.6+.

## Installation

There are two versions of MMCV:

- **mmcv-full**: comprehensive, with full features and various CUDA ops out of box. It takes longer time to build.
- **mmcv**: lite, without CUDA ops but all other features, similar to mmcv\<1.0.0. It is useful when you do not need those CUDA ops.

**Note**: Do not install both versions in the same environment, otherwise you may encounter errors like `ModuleNotFound`. You need to uninstall one before installing the other. `Installing the full version is highly recommended if CUDA is available`.

a. Install the full version.

Before installing mmcv-full, make sure that PyTorch has been successfully installed following the [official guide](https://pytorch.org/).

We provide pre-built mmcv packages (recommended) with different PyTorch and CUDA versions to simplify the building for **Linux and Windows systems**. In addition, you can run [check_installation.py](.dev_scripts/check_installation.py) to check the installation of mmcv-full after running the installation commands.

i. Install the latest version.

The rule for installing the latest `mmcv-full` is as follows:
xiabo's avatar
xiabo committed
93
94

```shell
limm's avatar
limm committed
95
pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/{cu_version}/{torch_version}/index.html
96
97
```

limm's avatar
limm committed
98
99
100
101
102
103
Please replace `{cu_version}` and `{torch_version}` in the url to your desired one. For example,
to install the latest `mmcv-full` with `CUDA 11.1` and `PyTorch 1.9.0`, use the following command:

```shell
pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu111/torch1.9.0/index.html
```
xiabo's avatar
xiabo committed
104

limm's avatar
limm committed
105
**Note**: mmcv-full is only compiled on PyTorch 1.x.0 because the compatibility usually holds between 1.x.0 and 1.x.1. If your PyTorch version is 1.x.1, you can install mmcv-full compiled with PyTorch 1.x.0 and it usually works well. For example, if your PyTorch version is 1.8.1 and CUDA version is 11.1, you can use the following command to install mmcv-full.
xiabo's avatar
xiabo committed
106

xiabo's avatar
xiabo committed
107
```shell
limm's avatar
limm committed
108
pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu111/torch1.8.0/index.html
Zaida Zhou's avatar
Zaida Zhou committed
109
110
```

limm's avatar
limm committed
111
112
113
114
115
116
For more details, please refer the the following tables and delete `=={mmcv_version}`.

ii. Install a specified version.

The rule for installing a specified `mmcv-full` is as follows:

xiabo's avatar
xiabo committed
117
```shell
limm's avatar
limm committed
118
pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/{cu_version}/{torch_version}/index.html
xiabo's avatar
xiabo committed
119
```
limm's avatar
limm committed
120
121
122
123
124
125
126

First of all, please refer to the Releases and replace `{mmcv_version}` a specified one. e.g. `1.3.9`.
Then replace `{cu_version}` and `{torch_version}` in the url to your desired versions. For example,
to install `mmcv-full==1.3.9` with `CUDA 11.1` and `PyTorch 1.9.0`, use the following command:

```shell
pip install mmcv-full==1.3.9 -f https://download.openmmlab.com/mmcv/dist/cu111/torch1.9.0/index.html
xiabo's avatar
xiabo committed
127
```
xiabo's avatar
xiabo committed
128

limm's avatar
limm committed
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
For more details, please refer the the following tables.

<table class="docutils">
  <tbody>
    <tr>
      <th width="80"> CUDA </th>
      <th valign="bottom" align="left" width="120">torch 1.11</th>
      <th valign="bottom" align="left" width="120">torch 1.10</th>
      <th valign="bottom" align="left" width="120">torch 1.9</th>
      <th valign="bottom" align="left" width="120">torch 1.8</th>
      <th valign="bottom" align="left" width="120">torch 1.7</th>
      <th valign="bottom" align="left" width="120">torch 1.6</th>
      <th valign="bottom" align="left" width="120">torch 1.5</th>
    </tr>
    <tr>
      <td align="left">11.5</td>
      <td align="left"><details><summary> install </summary><pre><code>pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu115/torch1.11.0/index.html</code></pre> </details></td>
      <td align="left"></td>
      <td align="left"></td>
      <td align="left"> </td>
      <td align="left"> </td>
      <td align="left"> </td>
      <td align="left"> </td>
    </tr>
    <tr>
      <td align="left">11.3</td>
      <td align="left"><details><summary> install </summary><pre><code>pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu113/torch1.11.0/index.html</code></pre> </details></td>
      <td align="left"><details><summary> install </summary><pre><code>pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu113/torch1.10.0/index.html</code></pre> </details></td>
      <td align="left"></td>
      <td align="left"></code></pre> </details> </td>
      <td align="left"> </td>
      <td align="left"> </td>
      <td align="left"> </td>
    </tr>
    <tr>
      <td align="left">11.1</td>
      <td align="left"> </td>
      <td align="left"><details><summary> install </summary><pre><code>pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu111/torch1.10.0/index.html</code></pre> </details> </td>
      <td align="left"><details><summary> install </summary><pre><code>pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu111/torch1.9.0/index.html</code></pre> </details> </td>
      <td align="left"><details><summary> install </summary><pre><code>pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu111/torch1.8.0/index.html</code></pre> </details> </td>
      <td align="left"> </td>
      <td align="left"> </td>
      <td align="left"> </td>
    </tr>
    <tr>
      <td align="left">11.0</td>
      <td align="left"> </td>
      <td align="left"> </td>
      <td align="left"> </td>
      <td align="left"> </td>
      <td align="left"><details><summary> install </summary><pre><code>pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu110/torch1.7.0/index.html</code></pre> </details> </td>
      <td align="left"> </td>
      <td align="left"> </td>
    </tr>
    <tr>
      <td align="left">10.2</td>
      <td align="left"><details><summary> install </summary><pre><code>pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu102/torch1.11.0/index.html</code></pre> </details></td>
      <td align="left"><details><summary> install </summary><pre><code>pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu102/torch1.10.0/index.html</code></pre> </details></td>
      <td align="left"><details><summary> install </summary><pre><code>pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu102/torch1.9.0/index.html</code></pre> </details> </td>
      <td align="left"><details><summary> install </summary><pre><code>pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu102/torch1.8.0/index.html</code></pre> </details> </td>
      <td align="left"><details><summary> install </summary><pre><code>pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu102/torch1.7.0/index.html</code></pre> </details> </td>
      <td align="left"><details><summary> install </summary><pre><code>pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu102/torch1.6.0/index.html</code></pre> </details> </td>
      <td align="left"><details><summary> install </summary><pre><code>pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu102/torch1.5.0/index.html</code></pre> </details> </td>
    </tr>
    <tr>
      <td align="left">10.1</td>
      <td align="left"> </td>
      <td align="left"> </td>
      <td align="left"> </td>
      <td align="left"><details><summary> install </summary><pre><code> pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu101/torch1.8.0/index.html</code></pre> </details> </td>
      <td align="left"><details><summary> install </summary><pre><code> pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu101/torch1.7.0/index.html</code></pre> </details> </td>
      <td align="left"><details><summary> install </summary><pre><code> pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu101/torch1.6.0/index.html</code></pre> </details> </td>
      <td align="left"><details><summary> install </summary><pre><code> pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu101/torch1.5.0/index.html</code></pre> </details> </td>
    </tr>
    <tr>
      <td align="left">9.2</td>
      <td align="left"> </td>
      <td align="left"> </td>
      <td align="left"> </td>
      <td align="left"> </td>
      <td align="left"><details><summary> install </summary><pre><code> pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu92/torch1.7.0/index.html</code></pre> </details> </td>
      <td align="left"><details><summary> install </summary><pre><code> pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu92/torch1.6.0/index.html</code></pre> </details> </td>
      <td align="left"><details><summary> install </summary><pre><code> pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cu92/torch1.5.0/index.html</code></pre> </details> </td>
    </tr>
    <tr>
      <td align="left">cpu</td>
      <td align="left"><details><summary> install </summary><pre><code> pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cpu/torch1.11.0/index.html</code></pre> </details></td>
      <td align="left"><details><summary> install </summary><pre><code> pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cpu/torch1.10.0/index.html</code></pre> </details> </td>
      <td align="left"><details><summary> install </summary><pre><code> pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cpu/torch1.9.0/index.html</code></pre> </details> </td>
      <td align="left"><details><summary> install </summary><pre><code> pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cpu/torch1.8.0/index.html</code></pre> </details> </td>
      <td align="left"><details><summary> install </summary><pre><code> pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cpu/torch1.7.0/index.html</code></pre> </details> </td>
      <td align="left"><details><summary> install </summary><pre><code> pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cpu/torch1.6.0/index.html</code></pre> </details> </td>
      <td align="left"><details><summary> install </summary><pre><code> pip install mmcv-full=={mmcv_version} -f https://download.openmmlab.com/mmcv/dist/cpu/torch1.5.0/index.html</code></pre> </details> </td>
    </tr>
  </tbody>
</table>

**Note**: The pre-built packages provided above do not include all versions of mmcv-full, you can click on the corresponding links to see the supported versions. For example, you can click [cu102-torch1.8.0](https://download.openmmlab.com/mmcv/dist/cu102/torch1.8.0/index.html) and you can see that `cu102-torch1.8.0` only provides 1.3.0 and above versions of mmcv-full. In addition, We no longer provide `mmcv-full` pre-built packages compiled with `PyTorch 1.3 & 1.4` since v1.3.17. You can find previous versions that compiled with PyTorch 1.3 & 1.4 [here](./docs/en/get_started/previous_versions.md). The compatibility is still ensured in our CI, but we will discard the support of PyTorch 1.3 & 1.4 next year.

**Note**: mmcv-full does not provide pre-built packages for `cu102-torch1.11` and `cu92-torch*` on Windows.

Another way is to compile locally by running

```python
pip install mmcv-full
limm's avatar
limm committed
234
```
limm's avatar
limm committed
235
236
237
238
239
240
241

Note that the local compiling may take up to 10 mins.

b. Install the lite version.

```python
pip install mmcv
limm's avatar
limm committed
242
```
limm's avatar
limm committed
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265

c. Install full version with custom operators for onnxruntime

- Check [here](docs/en/deployment/onnxruntime_op.md) for detailed instruction.

If you would like to build MMCV from source, please refer to the [guide](https://mmcv.readthedocs.io/en/latest/get_started/build.html).

## FAQ

If you face some installation issues, CUDA related issues or RuntimeErrors,
you may first refer to this [Frequently Asked Questions](https://mmcv.readthedocs.io/en/latest/faq.html).

## Citation

If you find this project useful in your research, please consider cite:

```latex
@misc{mmcv,
    title={{MMCV: OpenMMLab} Computer Vision Foundation},
    author={MMCV Contributors},
    howpublished = {\url{https://github.com/open-mmlab/mmcv}},
    year={2018}
}
Zaida Zhou's avatar
Zaida Zhou committed
266
```
xiabo's avatar
xiabo committed
267

limm's avatar
limm committed
268
## Contributing
Zaida Zhou's avatar
Zaida Zhou committed
269

limm's avatar
limm committed
270
We appreciate all contributions to improve MMCV. Please refer to [CONTRIBUTING.md](CONTRIBUTING.md) for the contributing guideline.
xiabo's avatar
xiabo committed
271

limm's avatar
limm committed
272
## License
limm's avatar
limm committed
273

limm's avatar
limm committed
274
MMCV is released under the Apache 2.0 license, while some specific operations in this library are with other licenses. Please refer to [LICENSES.md](LICENSES.md) for the careful check, if you are using our code for commercial matters.